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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Written text as operational data\n",
+ "\n",
+ "Written text is one type of data\n",
+ "\n",
+ "### Why people write?\n",
+ "\n",
+ " - To communicate: their thoughts, feelings, urgency, needs, information\n",
+ "\n",
+ "### Why people communicate?\n",
+ "\n",
+ "1. To express emotions\n",
+ "1. To share information\n",
+ "1. To enable or elicit an action\n",
+ "1. ...\n",
+ "\n",
+ "### We will use written text for the purpose other than \n",
+ "1. To experience emotion\n",
+ "1. To learn something the author intended us to learn\n",
+ "1. To do what the author intended us to do\n",
+ "\n",
+ "### Instead, we will use written text to recognize who wrote it\n",
+ " - By calculating and comparing word frequencies in written documents\n",
+ " \n",
+ "See, for example, likely fictional story https://medium.com/@amuse/how-the-nsa-caught-satoshi-nakamoto-868affcef595"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Example 1. Dictionaries in python (associative arrays)\n",
+ "\n",
+ "Plot the frequency distribution of words on a web page."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\t1\n",
+ "
You\t1\n",
+ "don't\t1\n",
+ "have\t1\n",
+ "permission\t1\n",
+ "to\t1\n"
+ ]
+ }
+ ],
+ "source": [
+ "import requests, re\n",
+ "# re is a module for regular expressions: to detect various combinations of characters\n",
+ "import operator\n",
+ "\n",
+ "# Start from a simple document\n",
+ "r = requests .get('http://eecs.utk.edu')\n",
+ "\n",
+ "# What comes back includes headers and other HTTP stuff, get just the body of the response\n",
+ "t = r.text\n",
+ "\n",
+ "# obtain words by splitting a string using as separator one or more (+) space/like characters (\\s) \n",
+ "wds = re.split('\\s+',t)\n",
+ "\n",
+ "# now populate a dictionary (wf)\n",
+ "wf = {}\n",
+ "for w in wds:\n",
+ " if w in wf: wf [w] = wf [w] + 1\n",
+ " else: wf[w] = 1\n",
+ "\n",
+ "# dictionaries can not be sorted, so lets get a sorted *list* \n",
+ "wfs = sorted (wf .items(), key = operator .itemgetter (1), reverse=True) \n",
+ "\n",
+ "# lets just have no more than 15 words \n",
+ "ml = min(len(wfs),15)\n",
+ "for i in range(1,ml,1):\n",
+ " print (wfs[i][0]+\"\\t\"+str(wfs[i][1])) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Example 2\n",
+ "\n",
+ "Lots of markup in the output, lets remove it --- \n",
+ "\n",
+ "use BeautifulSoup and nltk modules and practice some regular expressions."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import requests, re, nltk\n",
+ "from bs4 import BeautifulSoup\n",
+ "from nltk import clean_html\n",
+ "from collections import Counter\n",
+ "import operator\n",
+ "\n",
+ "# we may not care about the usage of stop words\n",
+ "stop_words = nltk.corpus.stopwords.words('english') + [\n",
+ " 'ut', '\\'re','.', ',', '--', '\\'s', '?', ')', '(', ':', '\\'',\n",
+ " '\\\"', '-', '}', '{', '&', '|', u'\\u2014' ]\n",
+ "\n",
+ "# We most likely would like to remove html markup\n",
+ "def cleanHtml (html):\n",
+ " from bs4 import BeautifulSoup\n",
+ " soup = BeautifulSoup(html, 'html.parser')\n",
+ " return soup .get_text()\n",
+ "\n",
+ "# We also want to remove special characters, quotes, etc. from each word\n",
+ "def cleanWord (w):\n",
+ " # r in r'[.,\"\\']' tells to treat \\ as a regular character \n",
+ " # but we need to escape ' with \\'\n",
+ " # any character between the brackets [] is to be removed \n",
+ " wn = re.sub('[,\"\\.\\'&\\|:@>*;/=]', \"\", w)\n",
+ " # get rid of numbers\n",
+ " return re.sub('^[0-9\\.]*$', \"\", wn)\n",
+ " \n",
+ "# define a function to get text/clean/calculate frequency\n",
+ "def get_wf (URL):\n",
+ " # first get the web page\n",
+ " r = requests .get(URL)\n",
+ " \n",
+ " # Now clean\n",
+ " # remove html markup\n",
+ " t = cleanHtml (r .text) .lower()\n",
+ " \n",
+ " # split string into an array of words using any sequence of spaces \"\\s+\" \n",
+ " wds = re .split('\\s+',t)\n",
+ " \n",
+ " # remove periods, commas, etc stuck to the edges of words\n",
+ " for i in range(len(wds)):\n",
+ " wds [i] = cleanWord (wds [i])\n",
+ " \n",
+ " # If satisfied with results, lets go to the next step: calculate frequencies\n",
+ " # We can write a loop to create a dictionary, but \n",
+ " # there is a special function for everything in python\n",
+ " # in particular for counting frequencies (like function table() in R)\n",
+ " wf = Counter (wds)\n",
+ " \n",
+ " # Remove stop words from the dictionary wf\n",
+ " for k in stop_words:\n",
+ " wf. pop(k, None)\n",
+ " \n",
+ " #how many regular words in the document?\n",
+ " tw = 0\n",
+ " for w in wf:\n",
+ " tw += wf[w] \n",
+ " \n",
+ " \n",
+ " # Get ordered list\n",
+ " wfs = sorted (wf .items(), key = operator.itemgetter(1), reverse=True)\n",
+ " ml = min(len(wfs),15)\n",
+ "\n",
+ " #Reverse the list because barh plots items from the bottom\n",
+ " return (wfs [ 0:ml ] [::-1], tw)\n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
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+ "